Limetest는 CI 워크플로에서 실행할 수 있는 AI 기능을 갖춘 가장 가벼운 엔드 투 엔드 테스트 프레임워크입니다. 테스트 케이스를 자연어로 정의하고 AI가 실행을 처리하도록 하세요.
AI에 최적화 : 테스트 사례를 일반 언어로 정의하고 AI가 처음부터 끝까지 실행하도록 합니다.
가볍고 효율적 : 픽셀 분석 대신 Playwright 스냅샷을 활용하여 더 빠르고 안정적인 실행을 제공합니다.
비전 기능 : 보다 정교한 테스트 시나리오에서 스냅샷 모드가 실패하면 비전 모드로 돌아갑니다.
지엑스피1
limtest는 새 프로필을 사용하여 Chrome 브라우저를 시작합니다.
- `%USERPROFILE%\AppData\Local\ms-limetest\mcp-chrome-profile` on Windows
- `~/Library/Caches/ms-limetest/mcp-chrome-profile` on macOS
- `~/.cache/ms-limetest/mcp-chrome-profile` on LinuxRelated MCP server: Playwright MCP
CI 워크플로에서 헤드리스로 테스트를 실행하려면 --headless를 사용하세요.
npx limetest examplehttps://github.com/user-attachments/assets/b801f239-dc66-4b3b-bcf2-42e2a9a68721
Playwright 가 지원하는 MCP(Model Context Protocol) 서버는 MCP 클라이언트에 대한 종단 간 테스트를 간소화합니다.
LLM이 계획하고 실행하는 자동화된 테스트
이 리포를 복제한 후 다음과 같이 E2E MCP 서버를 빌드하여 MCP 클라이언트에 추가합니다. 이 MCP 서버를 엔드 투 엔드 모드로 실행하려면 OpenAI API 키가 필요합니다.
npm install @limetest/mcp
npx playwright install그 다음에:
{
"mcpServers": {
"limetest": {
"command": "npx",
"args": [
"npx @limetest/mcp",
"--api-key=<your openai api key>"
]
}
}
}로그인한 모든 정보는 해당 프로필에 저장되며, 오프라인 상태를 지우려면 세션 간에 해당 정보를 삭제할 수 있습니다.
Limetest는 Microsoft Playwright MCP를 기반으로 하며, 독립형 프레임워크로서 자동화된 엔드투엔드 테스트에 최적화되어 있습니다. 이 프로젝트는 Apache 2.0 라이선스에 따라 배포됩니다.
Run an end to end test suit in the browser
| Name | Required | Description | Default |
|---|---|---|---|
| testDefinition | Yes | The test case definition |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'run' which implies execution, but doesn't describe what happens during the test (e.g., browser behavior, timeouts, outputs, or side effects). This leaves significant gaps in understanding the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, straightforward sentence that efficiently conveys the core purpose. However, the typo 'suit' (likely meant 'suite') slightly detracts from clarity, preventing a perfect score.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is insufficient for a tool that executes tests. It doesn't explain what 'run' entails (e.g., whether it returns results, logs, or errors), leaving the agent without key operational context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with the single parameter 'testDefinition' documented as 'The test case definition'. The description doesn't add any meaning beyond this, such as format examples or constraints. Since the schema does the heavy lifting, the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Run an end to end test suit in the browser' clearly states the action (run) and target (end to end test suit in the browser). It's specific enough to understand the tool's function, though 'test suit' appears to be a typo (likely 'test suite'). Since there are no sibling tools, differentiation isn't needed, so it doesn't reach the highest score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, prerequisites, or context for its application. It merely states what the tool does without indicating scenarios or constraints for its use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v1.0.0browser_endtoendScored across 1 tool
With only one tool, there is no possibility of ambiguity or overlap between tools. The tool's purpose is clearly defined and distinct by default.
A single tool inherently has perfect naming consistency, as there are no other tools to compare it against. The name 'browser_endtoend' follows a clear snake_case pattern.
One tool is too few for a server's purpose, as it severely limits functionality and suggests an incomplete or trivial implementation. This is a borderline case leaning toward inadequacy.
The server is severely incomplete; with only a single end-to-end test tool, there are obvious gaps in functionality for any meaningful domain, such as setup, teardown, or other testing operations.
A Model Context Protocol server for Wix AI tools
A comprehensive Model Context Protocol (MCP) server that enables AI assistants to interact with yo…
MCP server for Mint — AI-powered QA that runs your app in a real browser on every PR.
Enable secure connectivity between Sentry issues and debugging data, and LLM clients, using a Model Context Protocol (MCP) server.
